Systems for determining insulin on board and recommending insulin therapy, and related methods

ABSTRACT

A system is provided with an insulin delivery device configured to deliver insulin to a user of the system and a computer-based control unit associated with the insulin delivery device. The computer-based control unit includes a user interface and a computer-based processor. The computer-based processor is configured to calculate a relative insulin on board value for a specific time by calculating a first value that represents a reference insulin on board value at the specific time, calculating a second value that represents an automated insulin on board value at the specific time, and subtracting one of the first and second values from the other. The automated insulin on board value represents at least one insulin delivery automatically specified by the computer-based control unit. Methods of use are also disclosed.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.16/213,799, filed Dec. 7, 2018, which will issue as U.S. Pat. No.11,376,362, on Jul. 5, 2022, which is a continuation of U.S. patentapplication Ser. No. 14/733,567, filed Jun. 8, 2015, now U.S. Pat. No.10,188,793, issued Jan. 29, 2019, entitled “INSULIN DELIVERY SYSTEMS ANDMETHODS,” which claims the benefit of U.S. Provisional Application No.62/010,385, filed Jun. 10, 2014 and entitled “INSULIN DELIVERY SYSTEMSAND METHODS,” the entire contents and disclosure of which are herebyincorporated by this reference.

INCORPORATION BY REFERENCE

This application is related to U.S. patent application Ser. No.14/254,684 filed Apr. 16, 2014 and entitled “Discretionary InsulinDelivery Systems and Methods”, and U.S. patent application Ser. No.13/738,466 filed Jan. 10, 2013, now U.S. Pat. No. 9,833,191, issued Dec.5, 2017, and entitled “Computer-Based Diabetes Management”. Allpublications and patent applications mentioned in this specification areherein incorporated by reference to the same extent as if eachindividual publication or patent application was specifically andindividually indicated to be incorporated by reference.

TECHNICAL FIELD

This disclosure relates to the delivery of insulin to a user (e.g., aperson with diabetes) and, more particularly, this disclosure relates tosystems and methods for determining dosages of insulin to be deliveredto a user.

BACKGROUND

Diabetes mellitus is a chronic metabolic disorder caused by an inabilityof a person's pancreas to produce sufficient amounts of insulin, suchthat the person's metabolism is unable to provide for the properabsorption of sugar and starch. This failure leads to hyperglycemia,i.e., the presence of an excessive amount of analyte within the bloodplasma. Persistent hyperglycemia has been associated with a variety ofserious symptoms and life threatening long term complications such asdehydration, ketoacidosis, diabetic coma, cardiovascular diseases,chronic renal failure, retinal damage and nerve damages with the risk ofamputation of extremities. Because healing is not yet possible, apermanent therapy is necessary which provides constant glycemic controlin order to constantly maintain the level of blood analyte within normallimits. Such glycemic control is achieved by regularly supplyingexternal drugs to the body of the patient to thereby reduce the elevatedlevels of blood analyte.

An external biologically effective drug (e.g., insulin or its analog)was commonly administered by means of multiple, daily injections of amixture of rapid and intermediate acting drug via a hypodermic syringe.While this treatment does not require the frequent estimation of bloodanalyte, it has been found that the degree of glycemic controlachievable in this way is suboptimal because the delivery is unlikephysiological drug production, according to which drug(s) enters thebloodstream at a lower rate and over a more extended period of time.

Improved glycemic control may be achieved by the so-called intensivedrug therapy which is based on multiple daily injections, including oneor two injections per day of a long acting drug for providing basal drugand additional injections of a rapidly acting drug before each meal inan amount proportional to the size of the meal. Although traditionalsyringes have at least partly been replaced by drug pens, the frequentinjections are nevertheless very inconvenient for the patient,particularly those who are incapable of reliably self-administeringinjections.

Substantial improvements in diabetes therapy have been achieved by thedevelopment of other drug delivery devices, such as insulin pumps,relieving the patient of the need for syringes or drug pens and theadministration of multiple, daily injections. Insulin pumps allow forthe delivery of insulin in a manner that bears greater similarity to thenaturally occurring physiological processes and can be controlled tofollow standard or individually modified protocols to give the patientbetter glycemic control.

In addition, delivery directly into the intraperitoneal space orintravenously can be achieved by drug delivery devices. Drug deliverydevices can be constructed as an implantable device for subcutaneousarrangement or can be constructed as an external device with an infusionset for subcutaneous infusion to the patient via the transcutaneousinsertion of a catheter, cannula or a transdermal drug transport such asthrough a patch. External drug delivery devices are mounted on clothing,hidden beneath or inside clothing, or mounted on the body and aregenerally controlled via a user interface built-in to the device or on aseparate remote device.

Drug delivery devices have been utilized to assist in the management ofdiabetes by infusing drug or a suitable biologically effective materialinto the diabetic patient at a basal rate with additional drug or“bolus” to account for meals or high analyte values, levels orconcentrations. The drug delivery device typically is connected to aninfuser, better known as an infusion set by a flexible hose. The infusertypically has a subcutaneous cannula, and an adhesive backed mount onwhich the cannula is attached. The cannula may include a quickdisconnect to allow the cannula and mount to remain in place on the skinsurface of the user while the flexible tubing is disconnected from theinfuser. Regardless of the type of drug delivery device, blood analytemonitoring is typically required to achieve acceptable glycemic control.For example, delivery of suitable amounts of drug by the drug deliverydevice requires that the patient frequently determine his or her bloodanalyte level and manually input this value into a user interface forthe external drug delivery device, which then may calculate a suitablemodification to the default or currently in-use drug delivery protocol,i.e., dosage and timing, and subsequently communicates with the drugdelivery device to adjust its operation accordingly. The determinationof blood analyte concentration is typically performed by means of anepisodic measuring device such as a hand-held electronic meter whichreceives blood samples via enzyme-based test strips and calculates theblood analyte value based on the enzymatic reaction. In recent years,continuous analyte monitoring has also been utilized with drug deliverydevices to allow for greater control of the drug(s) being infused intothe diabetic patients.

In 1993, the landmark Diabetes Complications and Control Trial (DCCT)showed that intensive control of blood glucose not only reduces but alsocan prevent complications from Type 1 Diabetes. Post-DCCT health careprofessionals began prescribing a basal and bolus regimen of intensiveinsulin therapy to patients to help them maintain better glycemiccontrol.

Basal insulin is a constant or near constant dosage of insulin toprovide the body with insulin to allow for processing of glucose tomaintain the background metabolic function of the body. Basal insulincan be infused via a daily or twice daily dose of long-acting insulinwhere the insulin's availability and action is formulated to last for anextended period of time. Alternatively, the basal requirements of anindividual may be provided by a constant infusion of rapid actinginsulin analog via an insulin delivery device. An insulin bolus is aburst of rapid acting insulin to offset either a prandial event or tobring a patient's blood glucose level from hyperglycemia to the desired,target range. Typically, the bolus of insulin may be deliveredsubcutaneously through an insulin syringe, an insulin pen or via anotherinsulin delivery device such as an insulin pump.

A person in glucose stasis will tend to remain so in the absence of anymeal disturbances and if the person's acting basal insulin scheduleexactly offsets the person's background metabolic needs for insulin.When there is an excess of basal insulin at work, then the person'sblood glucose level will tend to decrease. A deficiency of basal insulinrelative to what the person's body requires will result in an increasein blood glucose level. Often, a person is first diagnosed with diabetesupon finding a higher than normal, fasting blood glucose level; this isa sign of insufficient endogenous insulin production.

In the years since the DCCT, patients with type 1 diabetes have oftenstruggled with managing the challenges of intensive insulin therapy.There are myriad variables that both affect a person's insulinrequirements and how their dosing should change on a day to day basisand even within a day. In light of the many deficiencies and problemsassociated with current systems and methods for maintaining properglycemic control, enormous resources have been put into finding bettersolutions. It has been contemplated for many years that it should beentirely feasible to couple a continuous glucose monitoring system withan insulin delivery device to provide some level of automation to themanagement of insulin delivery to people with diabetes. The effort inthis domain has ranged from semi-automated systems to fully automateddelivery systems; however, most systems have at least some level of userinteraction. Further, in any of these systems, the user's role changesfrom direct actor to supervisor of the automated system. As such, theuser requires new and different tools for overseeing such automation.The present disclosure includes novel systems and methods that assistthe user in understanding and visualizing what actions automated insulindelivery systems are taking in an effort to maintain the patient'sglycemic control.

BRIEF SUMMARY

According to some aspects of the disclosure, systems and methods areprovided to assist a user of insulin therapy in using semi-automated andautomated insulin delivery systems. The disclosure describes methods toquantify and visualize an arbitrary set of automated delivery actions aswell as user programmed delivery actions.

In some embodiments, the methods compare the automated delivery actionsto a reference insulin delivery schedule to calculate an estimated netamount of historical dosing action. This estimated amount may be used inthe calculation of a bolus amount or may also be used to visualize thefuture effects of the automated dosing.

In some embodiments, a system is provided with an insulin deliverydevice and a computer-based control unit. The insulin delivery device isconfigured to deliver insulin to a user of the system. Thecomputer-based control unit is associated with the insulin deliverydevice and includes a user interface and a computer-based processor. Thecomputer-based processor is configured to calculate a relative insulinon board value for a specific time. It does this by calculating a firstvalue that represents a reference insulin on board value at the specifictime. It also calculates a second value that represents an automatedinsulin on board value at the specific time. The computer-basedprocessor subtracts one of the first and second values from the other.The automated insulin on board value represents at least one insulindelivery automatically specified by the computer-based control unit.

In some of the above embodiments, the relative insulin on boardcalculation further includes adding a non-automated insulin on boardvalue to the automated insulin on board value when calculating thesecond value. The non-automated insulin on board value represents atleast one insulin delivery manually specified by the user or acaregiver. In some embodiments, the relative insulin on boardcalculation takes into account all insulin delivered to the user priorto the specific time that is believed to not have been completelyabsorbed by the user prior to the specific time, including any and allbasal doses delivered to the user.

In some embodiments, a glucose monitor is configured to measure glucosevalues of the user. The glucose monitor is configured to automaticallytransfer the glucose values to the computer-based control unit. Thecomputer-based control unit is configured with a mode to automaticallycontrol insulin delivery to the user through the insulin deliverydevice, thereby forming an automatic feedback control loop.

In some embodiments, the computer-based processor is configured tocalculate the relative insulin on board value by subtracting the firstvalue from the second value. The calculation of the first value mayinclude all insulin delivered according to a reference insulin deliveryschedule and the second value may include all insulin deliveredaccording to an automated insulin delivery schedule. The referenceinsulin on board value may be greater than the automated insulin onboard value. In some embodiments, the computer-based control unit isconfigured to display the relative insulin on board value on the userinterface to the user or a caregiver. The computer-based control unitmay be configured to display a function of the relative insulin on boardvalue as it is calculated to vary over a time period. In someembodiments at least a portion of the time period is a future time. Thecomputer-based control unit may also be configured to calculate anddisplay a predicted change in glucose levels based on the function ofthe relative insulin on board value. In some embodiments, thecomputer-based control unit is configured to calculate a future insulindelivery schedule based in part on the relative insulin on board valuecalculated by the computer-based processor. The insulin delivery devicemay be configured to deliver insulin to the user of the system accordingto the calculated future insulin delivery schedule.

In some embodiments, a system is provided with an insulin deliverydevice and a computer-based control unit. The insulin delivery device isconfigured to deliver insulin to a user of the system. Thecomputer-based control unit is associated with the insulin deliverydevice and includes a user interface and a computer-based processor. Thecomputer-based processor is configured to calculate a relative insulinon board value over a period of time. This is accomplished by firstcalculating a difference-dosing-schedule. The difference-dosing-scheduleis calculated by using a first schedule that represents a referencedosing and a second schedule that represents an automated dosing at eachof a plurality of time points in the period of time. At each of theplurality of time points, one of the first and second schedule values atthe time point is subtracted from the other. The relative insulin onboard is then obtained by calculating an insulin on board value for thedifference-dosing-schedule by summing an insulin on board for each ofthe plurality of time points. The automated dosing represents at leastone insulin delivery automatically specified by the computer-basedcontrol unit.

In some of the above embodiments, the system further comprises a glucosemonitor configured to measure glucose values of the user. The glucosemonitor is configured to automatically transfer the glucose values tothe computer-based control unit. The computer-based control unit isconfigured with a mode to automatically control insulin delivery to theuser through the insulin delivery device, thereby forming an automaticfeedback control loop.

In some embodiments, an insulin delivery device is provided with aninsulin delivery mechanism and a computer-based control unit. Theinsulin delivery mechanism is configured to deliver insulin to a user ofthe device. The computer-based control unit is coupled to the insulindelivery mechanism to automatically deliver insulin to the user. Thecomputer-based control unit has a user interface and a computer-basedprocessor. The computer-based processor is configured to calculate arelative insulin on board value associated with a specific time period.This is accomplished by calculating a first value that represents areference insulin on board value associated with the specific timeperiod. A second value is calculated that represents an automatedinsulin on board value associated with the specific time period. One ofthe first and second values is subtracted from the other. The automatedinsulin on board value represents at least one insulin deliveryautomatically specified by the computer-based control unit. Thereference insulin on board value may be greater than the automatedinsulin on board value. The computer-based control unit is configured todisplay the relative insulin on board value on the user interface to theuser or a caregiver.

In some of the embodiments, the computer-based control unit furthercomprises a bolus calculator configured to assist the user or acaregiver with calculating a bolus dosage of insulin to be delivered tothe user. The bolus calculator is configured to use the calculatedrelative insulin on board value in determining a proper bolus dosage.

In some embodiments, a method of delivering insulin to a user isprovided. The method includes providing an insulin delivery deviceconfigured to deliver insulin to a user of the system. The methodfurther includes providing a computer-based control unit associated withthe insulin delivery device. The computer-based control unit has a userinterface and a computer-based processor. The method further includescalculating a relative insulin on board value for a specific time. Thisis accomplished by calculating a first value that represents a referenceinsulin on board value at the specific time. A second value thatrepresents an automated insulin on board value at the specific time isalso calculated. One of the first and second values is subtracted fromthe other. The automated insulin on board value represents at least oneinsulin delivery automatically specified by the computer-based controlunit. The method further includes calculating an insulin dosage schedulebased in part on the calculated relative insulin on board value. Themethod also includes delivering insulin to the user according to thecalculated insulin dosage schedule.

In some of the above embodiments, the method further includes displayingthe calculated relative insulin on board value to the user or acaregiver on the user interface. The method may also include allowingthe user or a caregiver to manually enter an insulin dosage into thecomputer-based control unit through the user interface to besubsequently delivered to the user after the calculated relative insulinon board value has been displayed on the user interface. In someembodiments, the reference insulin on board value may be greater thanthe automated insulin on board value.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic view of an exemplary system adapted to implementone or more of the techniques disclosed herein.

FIG. 2A is a plot showing one implementation of insulin absorption formultiple values of duration of insulin action.

FIG. 2B is another plot showing linear implementation of insulinabsorption for multiple values of duration of insulin action.

FIG. 3 is an exemplary representation of the behavior of the system inFIG. 1 .

FIG. 4 is another exemplary representation of the behavior of the systemin FIG. 1 .

FIG. 5A illustrates an exemplary calculation of insulin on board for thesystem in FIG. 1 .

FIG. 5B illustrates an exemplary visualization of future glucose changesfor the system in FIG. 1 .

FIG. 6A illustrates another exemplary calculation of insulin on boardfor the system in FIG. 1 .

FIG. 6B illustrates another exemplary visualization of future glucosechanges for the system in FIG. 1 .

DETAILED DESCRIPTION

FIG. 1 is a schematic view of an exemplary system 100 adapted toimplement one or more of the techniques disclosed herein.

The illustrated system 100 includes a glucose monitoring/measuringdevice 102, an insulin delivery device such as an insulin pump (orinsulin delivery device) 104 and a controller 106. The controller 106has a user interface 108, an internal computer-based processor andinternal computer-based memory storage capacity.

In the illustrated implementation, the glucose monitoring/measuringdevice 102, the insulin pump 104 and the controller 106 are configuredso that they can communicate with each other using wirelesscommunication channels 110 a, 110 b (e.g., using wireless communicationtechnologies). However, in other implementations, information may betransferred between the components illustrated in FIG. 1 using a wiredconnection or may, in some instances, be transferred by the user orcaregiver him or herself. For example, if the glucosemonitoring/measuring device 102 is a monitor that simply presents bloodglucose reading on a visual display, for example, but is not able totransmit the reading directly to the controller 106, then the personusing the system 100 may view the displayed blood glucose reading andenter that reading manually at the controller 106. In otherimplementations (not shown), any one of the glucose monitoring/measuringdevice 102, the insulin pump 104 and the controller 106 can be combinedwith another of the devices in a single integrated unit, or all threemay be combined. For example, some implementations incorporate thecontroller 106 into the insulin delivery device 104. In combineddevices, insulin delivery protocols may be provided by a dedicatedcomputer-based processor, or a single processor may control the insulindelivery protocols, glucose monitoring, insulin delivery devicefunctions and/or user interface functions.

In various implementations, the glucose monitoring/measuring device 102can be a continuous glucose monitor, a blood glucose meter, anintravenous blood glucose measurement device, or other device adapted toprovide an indication of blood glucose levels in the user. In someimplementations, the level of glucose in the user's blood may never bedirectly measured. Rather, the glucose level in the user's interstitialfluid or other bodily fluid or tissue may be measured, and at some pointmay (or may not) be converted into an equivalent glucose level of wholeblood, plasma or serum. It is to be understood that the use herein ofthe terminology “blood glucose” level may mean actual blood glucoselevel or a surrogate glucose level, depending on the context.

The insulin “pump” 104 can be any type of insulin delivery device. Ingeneral, the insulin pump is a medical device used for theadministration of insulin, for example, in the treatment of diabetes.The pump can have a variety of possible configurations. In someimplementations, for example, the insulin pump 104 includes a pump (withcontrols, processing module, batteries, etc.), a disposable reservoirfor insulin (which may be inside the pump), and a disposable infusionset, including a cannula for subcutaneous insertion (under the skin) anda tubing system to interface the insulin reservoir to the cannula. Insome implementations, however, the pump may not include one or more ofthese components. For example, in some implementations, the pump willnot have tubing. Also, in some implementations, the pump will notinclude a disposable reservoir. In other configurations, the pump may becontrolled by a handheld device or by an application loaded onto amobile phone or other mobile computing device. It is to be understoodthat, depending on the context, the use herein of the terminology “pump”or “delivery device” may refer to conventional insulin pumps availableon the market today, or may refer to other insulin delivery devices suchas insulin pens, automated inhalers, variable rate insulin skin patchesand other such delivery devices, whether or not they are commerciallyavailable today. It is envisioned that the devices, systems and methodsdisclosed herein may also be applied to other insulin delivery methods,such as intravenous insulin delivery in an intensive care unit, and mayalso find use in delivering other medicines or fluids to a user. In suchother systems, analyte(s) other than glucose may be monitored in auser's body to aid in determining the desired amount of medicine orfluid to be delivered to the user.

The controller 106 can be any type of computer-based device configuredto implement and/or facilitate the functionalities disclosed herein. Insome implementations, the controller 106 is a smartphone executing theAndroid™ operating system. However, the controller 106 can be any typeof smartphone (or other device) executing any type of operating system.In general, a smartphone is a mobile phone built on a mobile operatingsystem, with more advanced computing capability connectivity than afeature phone. Many modern smartphones also include high-resolutiontouchscreens and web browsers that display web pages. High-speed dataaccess can be provided by Wi-Fi and/or mobile broadband. In a typicalimplementation, the insulin delivery device 104 is adapted to deliverinsulin to a user (e.g., a person with diabetes). Typically, the userhas the ability to set a default basal insulin delivery schedule toprovide a continuous, background dose of insulin to provide for thebasic metabolic needs of the individual. The basal delivery, once set,will provide the pre-programmed dose of insulin unless directedotherwise by the user such as by suspending delivery or by instructingthe insulin pump to deliver a temporary basal rate which differs fromthe pre-programmed rate for a period of time. A typical insulin pumpimplementation is also adapted to allow the user to program bolus dosesof insulin, either to be delivered immediately or to be spread over aperiod of time, sometimes referred to as an extended bolus.

Semi-automated or automated systems may have a variety of modes in whichthey can operate. Typically, one of these modes is a default orzero-automation mode where the system provides no automation and theuser is wholly responsible for their insulin dosing. In the defaultmode, an automated system provides a schedule of basal insulin deliverythat we refer to as the default basal delivery program. The default modemay be triggered, for example, when the system does not have acontinuous glucose sensor actively providing glucose information. Or itmay be the result of some other condition that the system deems unsafefor automated delivery such as a degraded continuous glucose sensorsignal.

The determination of what the default basal delivery program is may varyacross implementations. In some implementations, the default basaldelivery schedule can be a fixed schedule of insulin delivery that theuser inputs. In other implementations, the system may vary the defaultbasal delivery schedule over time to optimize the basal insulin that isdelivered when the system operates in its default, zero-automation mode.In some implementations, the default basal program includes or consistsof a vector of day-time pairs coupled with a rate of insulin deliverybetween that time period and the next time period.

As used herein, a “user” is typically a person who receives insulin fromthe inventive devices, systems and methods disclosed herein. In someimplementations, actions may be performed by a “caregiver” who is aperson or persons different from the “user”. For example, the caregivermay be a parent, other family member, teacher, physician, clinician,advisor, or other person(s) assisting the user with management of his orher diabetes. In some implementations, actions ascribed to a caregivermust be performed by the caregiver(s) and may not be performed by theuser. In other implementations, the user and the caregiver are one andthe same person, and there is no other person directly involved in thedelivery of insulin to the user.

In some implementations, the system 100 provides for automated deliverymodes wherein the system is configured to automatically dose insulin.The automated or semi-automated algorithm that the system uses todetermine the amount of insulin to deliver at any point in time may varygreatly across implementations. In a typical implementation, however,the user will find it valuable to gain some understanding of the natureof the automated insulin delivery; how much or how little insulin isbeing delivered and at what time it has been delivered. For example, auser may find this information valuable if the automation is onlypartial automation and the user is still required to make insulin dosingdecisions concurrent with the automation. Another scenario where thisinformation may be useful is when the system 100 finds it necessary toturn off the automation and switch to a default insulin delivery modeafter which the user is solely responsible for managing the insulindelivery. In this situation, a user would find it helpful to understandwhat the automation has been doing up until the point of transition tomanual-mode.

A key metric that patients using intensive insulin therapy rely upon tounderstand their insulin dosing is an estimate of how much insulin hasbeen recently delivered to the user's body but has yet to act on theuser's blood glucose level. This quantity is commonly referred to asinsulin-on-board (IOB). The estimate of IOB is helpful to patientsbecause it can take hours after insulin is delivered for the bloodglucose lowering action of the insulin delivery to complete. During thistime period, it may prove beneficial to a user to incorporate knowledgeof this prior insulin delivery into the user's dosing decisions.

In a typical implementation, the system 100 can estimate IOB for theuser based on information about recent actual insulin deliveries fromthe insulin delivery device 104 and insulin absorption information(e.g., the user's insulin absorption curve, and the user's duration ofinsulin action (DIA) which defines how long it takes for 100%absorption, etc.) that may be specific to the user.

FIGS. 2A and 2B show illustrative examples of IOB absorption curves forvarious DIAs. The y-axes on the graphs show the fraction of insulinremaining on board from a dose of insulin and the x-axes show the hourselapsed since the delivery. Typically, the system 100 allows the user toconfigure the DIA to their specific insulin formulation and theirpersonal response rate. For example, curve 202 shows an exemplaryabsorption profile for a DIA of 3 hours while curve 204 shows anabsorption profile of 5 hours. The exemplary insulin action curves inFIG. 2A are adapted from Mudaliar, et al., “Insulin Aspart (B28Asp-Insulin): A Fast-Acting Analog of Human Insulin,” Diabetes Care22:1501-1506, 1999. Other implementations may use other action curvessuch as a linear absorption profile as shown in FIG. 2B.

In traditional systems without any automation (i.e., systems that onlyprovide a pre-programmed basal rate of insulin delivery and manuallyprogrammed bolus deliveries but no automated changes to the basal rateor automated bolus deliveries), insulin-on-board calculations typicallydo not include the basal rate insulin deliveries. Such basal deliveriestypically are intended to maintain the current blood glucose level, notto raise or to lower it, and not to offset the effect of a meal, etc.,as does a bolus delivery. As such, the basal rate of insulin can beconsidered an effective reference insulin delivery schedule that seeksto maintain static blood glucose levels. In implementations withautomation, a reference schedule of insulin delivery is a useful tool tocalculate the IOB of the automated deliveries.

A reference schedule of insulin delivery allows for incorporating bothincreases and reductions in insulin delivery into the IOB calculation.The methods described herein allow for a more complete understanding ofautomated or semi-automated insulin delivery by providing transparencyinto automated reductions in insulin delivery as well as increases indelivery. In some implementations, the default basal rate is used as areference insulin delivery schedule, while other implementations may usea different insulin delivery schedule that may or may not be related tothe default basal rate. Typically, the reference insulin deliveryschedule is, to the best of the system's knowledge, the schedule ofinsulin delivery that will maintain a constant level of blood glucose ina steady state condition.

Typically, traditional IOB calculations do not include basal deliverybecause the basal delivery matches the reference insulin deliveryschedule in these systems (to the best of the user's knowledge) and thusit should not have any effect (either to raise or to lower) on theuser's blood glucose level regardless of how much basal insulin is“on-board.” It follows that since the basal insulin deliveries are notexpected to affect the user's blood glucose level, they aren't relevantto future dosing recommendations and should not be included in IOBcalculations.

Considered another way, the reference insulin delivery schedule is theamount of insulin the system 100 would expect to exactly offset theuser's metabolic needs to maintain blood glucose stasis absent anydisturbances (such as meal, stress, etc.). Thus, although there may bebasal insulin that has been dosed but has not yet been absorbed, atypical implementation would not anticipate the basal insulin dose tohave any blood glucose lowering effect since it will be cancelled out bythe metabolic needs of the person.

Typically, the calculation of insulin-on-board may include some or allof the following: meal related bolus insulin; correction related bolusinsulin; extended bolus delivery; and, in some implementations, manuallyprogrammed temporary basal rates. A meal related bolus of insulin is apoint dose of insulin taken primarily to offset the consumption ofglucose increasing food such as carbohydrates. A correction relatedbolus delivery is a point in time dose of insulin that attempts tocorrect for a high blood glucose level back to the target range. Anextended or square wave bolus is a bolus that is evenly dosed over aperiod of time, usually to offset a longer absorption meal. A temporarybasal rate is a period of time when the user instructs the system 100 todeliver either more or less than the preset basal rate in the system.

Insulin on board for a point delivery of insulin (such as a bolus) maybe determined by multiplying the amount of the insulin delivery by thefraction of absorption remaining as determined by the time since thedelivery, the absorption curve and the DIA. A typical absorption curvewill define a fraction of insulin remaining on the y-axis by the timesince bolus on the x-axis as illustrated in FIGS. 2A and 2B.

FIG. 3 shows an exemplary IOB calculation for a 5 unit bolus taken at9:00 AM with the system configured to have a DIA of 4 hours. The y-axisis the insulin-on-board remaining from the bolus and the x-axis is thetime. At 9:00 AM, the IOB equals the full 5 units of insulin since thedose was just given. By 10:30 AM, the IOB remaining is about 2.5 units.According to the illustrated example, the full insulin action of thebolus tails off around 1:00 PM or 4 hours after the bolus was initiallygiven.

To calculate insulin on board for a continuous delivery of insulin suchas a basal delivery or an extended bolus, the continuous delivery ofinsulin may be discretized into very small bolus deliveries of insulin.For example, if an extended bolus is given to dose 6 units of insulinover the next hour, the extended bolus delivery can be discretized into60 boluses of 1/60th of the dose or 0.1 units each, delivered at minute1, 2, 3, . . . , 60 of the hour. The exact interval of thediscretization may vary across implementations and typically will worksufficiently well as long as the length of each sub-period is very smallrelative to the DIA. Once discretized, the IOB for each individualdiscretized bolus may be calculated as described above, and then summedtogether to compute the IOB for the entire continuous delivery. Duringthe continuous delivery, only doses that have already occurred would beincluded in this calculation. Alternatively, if an implementation'sinsulin action curve may be represented by a mathematical function, itis possible to perform the above discrete integral by mathematicallyintegrating the insulin action curve over the delivery period.

FIG. 4 illustrates the calculation of the IOB for the 6 unit extendedbolus delivery discussed above. The 1 hour extended bolus is started at5:00 PM with the DIA of the system 100 configured to be 5 hours. The IOBincreases between 5:00 PM and 6:00 PM as the insulin is dosed. At 6:00PM, the IOB is less than the full 6 units because some of the action ofthe insulin dosed between 5:00 PM and 6:00 PM has already completed. TheIOB drops to about 3 units remaining at approximately 7:15 PM showingthat about half of the absorption is complete at that time. The IOB doesnot return to 0 until around 11:00 PM when the 5 hour DIA for the finaldiscretized boluses at 6 PM complete.

In some implementations, the system 100 allows for semi-automated orautomated insulin dosing. As noted above, an implementation withautomation may compute the IOB for the insulin delivered as part of theautomated delivery. In some implementations, this IOB may be presentedas an independent automated delivery IOB calculation while in otherimplementations, the automated delivery IOB is summed with the other,manual delivery IOB calculations to give a net total IOB calculation.

To calculate the IOB for semi-automated or automated dosing systems,some implementations will compare the actual automated insulin dosinghistory to the reference delivery schedule over the automated deliverytime period to find the difference between the two. Typically, if theautomated insulin delivery differs from the reference insulin deliveryschedule, the system would expect there to be a residual blood glucoseeffect that should be reflected in an IOB calculation. This residualeffect may be either positive or negative depending on how much and whenthe automated dosing occurred relative to the reference insulindelivery. Calculating the IOB in this manner will be referred to as arelative-IOB.

For example, take an automated delivery that allows the basal rate tovary between x and y units per hour where the reference deliveryschedule would call for z units of basal delivery per hour. Someimplementations calculate a relative-IOB for this type of automateddelivery by computing the IOB for both the automated delivery(IOB_automated) and for the reference delivery over the same time period(IOB_reference) and then taking the difference,IOB_automated-IOB_reference to find the relative-IOB to assign to theperiod of the automated delivery. Typically, the IOB_automated andIOB_reference calculations will include all insulin dosing includingbasal insulin doses during the time period under consideration. The samecalculation may be performed by first taking the difference between theautomated delivery and the reference delivery schedules to create adifference-in-delivery schedule. The IOB may be calculated on thedifference-in-delivery schedule to compute the relative-IOB for theautomated delivery. That is, the relative-IOB calculation holds underthe distributive property of mathematics. It will be apparent to thoseof ordinary skill in this art that other variations to thesecalculations may be made without departing from the scope and spirit ofthe appended claims. Note that in cases where the IOB_automated is lessthan the IOB_reference, the relative-IOB calculated for such automateddelivery period is negative. A negative relative-IOB may be added to anyother IOB from other deliveries (positive or negative) in a simpleadditive manner to calculate the total IOB for the user.

A negative relative-IOB reflects that the user has received less insulinthan the reference delivery would have delivered. Since standard insulintherapy provides for the reference basal delivery to keep glucose valuesat static levels, the delivery of less than the reference basal deliveryresults in a deficit of insulin relative to what the user would need tokeep glucose levels static. This deficit results in an expectedsubsequent rise in glucose values. The magnitude of this expected riseequals the absolute value of the insulin deficit amount, orrelative-IOB, multiplied by the user's insulin sensitivity factor (ISF),where the ISF is the amount that a user's blood glucose level willdecrease when dosed with 1 unit of insulin.

In some implementations, the benefit of computing the relative-IOB of anautomated delivery is that it allows the user or caregiver to moreeasily understand and quantify what the net effect is of the therapychanges caused by a particular automated delivery. Depending on theimplementation and the scenario, the particular automated delivery maydeliver more or less than the reference delivery schedule. Therelative-IOB calculation allows the user to see if the net effect of theautomated delivery is an increase (positive IOB) or decrease (negativeIOB) to the reference insulin delivery schedule and what the magnitudeof such change is.

FIGS. 5A and 5B show an example relative-IOB calculation for a temporaryattenuation of insulin delivery. This scenario could occur for exampleduring an automated attenuation of insulin delivery or a manualtemporary basal rate set by the user. In the illustrated example, thebasal insulin delivery is attenuated by the automated system due to adecline in glucose levels. The DIA is configured to be 5 hours in theillustrated system.

Referring to FIGS. 5A and 5B the left y-axes show the calculatedrelative-IOB for the automated attenuation of delivery as illustrated byline 502. The x-axes show the time of day. The right y-axis in FIG. 5Ashows the rate of insulin delivery in units per hour. In thisillustrated example, the reference delivery rate is 1 unit per hour andthe automated delivery schedule is shown by dashed line of 504. Theright y-axis in FIG. 5B illustrates the cumulative expected change inblood glucose level for a user with an ISF of 50 mg/dL/unit, asillustrated by curve 506.

In the illustrated example, FIG. 5A shows the attenuation of insulincommences at 12:00 when the insulin delivery rate drops from 1 unit perhour to 0 units per hour. Line 502 shows that the absolute magnitude ofthe relative-IOB increases as the time period continues until 13:00where the attenuation ceases and the delivery rate once again matchesthe reference basal delivery rate of 1 unit per hour. In thisillustrated example, because the automated delivery is less than thereference delivery of 1 unit per hour, the calculated IOB for theautomated delivery is less than the calculated IOB for the referencedelivery. This results in a negative relative-IOB, implying that theblood glucose level is expected to rise as a result of the attenuationof insulin delivery.

FIG. 5B shows, in curve 506, the cumulative expected rise in bloodglucose level that is implied by the negative relative-IOB illustratedby line 502. The effects of the attenuation begin to appear atapproximately 12:40 when the effects of the first missing doses ofinsulin would have begun to act. The effect of the insulin attenuationincreases substantially between 13:00 and 15:00 and continues to showsmall effects until the DIA of the last missing dose is reached at about18:00.

The illustrated example shows how this relative information may beuseful to a user. In the case of an automated insulin deliveryattenuation, the missing insulin, relative to the reference delivery,will continue to have an effect for hours to come. If, for example, theautomated attenuation was a result of a user's blood glucose level beingnear hypoglycemic levels, the negative relative-IOB could give the userinformation that may be helpful in reducing or even to dispensing with acarbohydrate ingestion intervention to raise blood glucose levels sincethe relative-IOB already implies a future rise in blood glucose levels.In another scenario where the user plans to eat a meal, knowledge thatan insulin delivery attenuation may have already offset a low bloodglucose level may be helpful to a bolus calculator which would otherwisereduce the prandial insulin bolus to account for the low blood glucoselevel.

The incorporation of the future effects of an attenuation of insulinsuch as illustrated in FIGS. 5A and 5B are not possible with thestandard calculation of IOB that one will find discussed in prior art.The novel inclusion of both a reference insulin delivery schedule andthe actual insulin delivery in the calculation of the IOB allows forautomated attenuations of insulin to be seamlessly integrated into auser's bolus calculations and insulin therapy decisions. More accurateestimates of IOB will result in superior outcomes than in systems wheresuch reductions in insulin delivery are excluded from the IOBcalculation.

FIGS. 6A and 6B illustrate yet another example of the calculation ofrelative-IOB for automated insulin delivery. In the exemplary system,the system 100 is configured to have a DIA of 5 hours and a referencebasal delivery of 1 unit per hour. The x-axes show the time of day. Theleft y-axes show the calculated relative-IOB for the automated deliveryat each point in time, as illustrated by curve 602. The right y-axis inFIG. 6A shows the rate of automated insulin delivery as illustrated bydashed line 604, and the right y-axis in FIG. 6B shows the projectedcumulative change in glucose levels from the start of the example at11:00, as illustrated by curve 606.

Referring to FIG. 6A, we see that the automated system increases theinsulin delivery rate from the reference level of 1 unit per hour to 3units per hour at 11:30. This rate is held for 1 hour until 12:30. Asshown by curve 602, the relative-IOB at 12:30 has risen from 0 to almost2 units. The 2 units of IOB reflects the additional 2 units per hourthat the automated delivery has provided between 11:30 and 12:30 that isover and above the reference delivery rate. The relative-IOB is lessthan 2 units at 12:30 because some of the addition insulin delivered hasalready acted.

Between 12:30 and 13:00 the relative-IOB (see curve 602) decreases asthe insulin works to lower the blood glucose level as illustrated bycurve 606 in FIG. 6B. At 13:00, the system attenuates insulin deliveryto 0 units per hour. This immediately begins to decrease therelative-IOB for the user as can be seen by the sharp change in the rateof decline of curve 602 at 13:00. Between 13:00 and 14:30 the automateddelivery rate is 0. During this time period, the calculated relative-IOB(see curve 602) is decreasing rapidly as the initial augmented dosingacts on the glucose levels and the negative relative-IOB from theattenuation is added to the IOB calculation, both causing a decrease inthe net relative-IOB (see curve 602).

The change in glucose levels, as illustrated by curve 606 in FIG. 6B,continues to decrease even after the relative-IOB becomes negative justbefore 14:00. At this point, the glucose levels have been lowered byabout 56 mg/dL due to the initial increase in insulin dosing. As thenegative, relative-IOB (see curve 602) increases in magnitude, theeffects of the insulin attenuation turn the blood glucose level plot(see curve 606) to a positive slope. The projected change in glucoselevel (curve 606) reaches a nadir at approximately 14:30, after whichthe glucose levels shown by curve 606 increase in line with theremaining negative, relative-IOB (see curve 602) from the insulinattenuation.

The illustrated example provides a simple window into the power of howthe methods described herein can help to distill the salient effects ofa complex set of automated dosing history that a typical automated orsemi-automated implementation of the system 100 may engage in.Additionally, the methods may be used to combine both automated andmanual insulin dosing histories seamlessly. The methods are agnostic asto the agent, human or machine, that takes the dosing or attenuationaction. The methods described herein may be used to sum virtually anycombination of automated insulin dosing including, but not limited to:meal boluses; correction boluses; an increase or decrease in basal rate(either automated or manual); and extended boluses. The methods mayeffectively incorporate basal rate differences of any magnitude and thechanges in the exemplary systems in FIGS. 5A, 5B, 6A and 6B are forillustrative purposes only.

FIGS. 6A and 6B again show the limitations of prior art of IOBcalculation. A standard calculation of IOB only incorporates insulindosing greater than the pre-programmed basal rate (e.g., boluses) anddoes not take into account basal rate changes. As illustrated in FIGS.6A and 6B, an automated or semi-automated system may have a complex setof automated actions that includes both increases and decreases ofinsulin delivery relative to a reference insulin delivery schedule. Asystem without the ability to integrate both increases and attenuationsof insulin into the IOB calculation will not be able to accuratelyreport the true IOB in an individual. The methods described herein canincorporate virtually any combination of increased, decreased, automatedor manual dosing changes into the calculation of IOB and thus will be avaluable addition to the art and to future semi-automated and automatedsystems.

The methods may be further used to visualize the projected future actionof the prior dosing (automated, manual or a combination of the two) asshown by curves 506 and 606 in FIGS. 5B and 6B, respectively. The futureglucose level projections may be created by calculating the projectedchange in IOB at each future time period and then by multiplying thechange by the user's ISF. This multiplication will give a projectedchange in blood glucose level vector for each future period of time. Inthese implementations, the projected change in IOB for a time period isthe increase or decrease in IOB for all dosing adjustments administeredprior to the time period. The IOB for a future time may be calculatedusing the standard IOB calculation but using a future time in lieu ofthe present time for the insulin absorption lookup on the insulinabsorption curve. A cumulative projected glucose change curve such ascurves 506 and 606 in FIGS. 5B and 6B, respectively, may be calculatedby summing the set of future periods of interest.

In some implementations, the relative-IOB for automated dosing may beprovided to a user separate and apart from the IOB from the manuallyprogrammed user doses. In other implementations, all of the IOB' s forthe system are combined together to provide a net IOB for the user.These values may be particularly useful if integrated into a boluswizard or calculator.

A bolus calculator is a tool found in a typical insulin delivery devicethat helps a user to determine a correct insulin dose at a particularpoint in time based on a number of variables. The calculator may be usedto determine if a correction dose is required and/or how many units ofinsulin should be taken for a certain amount of carbohydrates to beingested. In a typical implementation, the bolus calculator uses auser's current blood glucose level, target glucose level, anticipatedcarbohydrates to be ingested and the current insulin on board for theuser. How these variables are used in the calculation of the suggestedbolus varies from implementation to implementation.

The use of the relative-IOB of automated dosing may be beneficial inmany cases for users of insulin bolus calculators. As described herein,the relative-IOB resulting from automated deliveries may have a materialeffect on a user's future blood glucose level and thus including it inthe bolus calculator may prove beneficial to the user. How therelative-IOB is used may vary among implementations: an implementationmay choose to combine all IOB or it may consider the human dosed IOBdifferently from the automated, relative-IOB. The introduction ofnegative IOB's may further differentiate how different implementationschoose to implement the information into their bolus recommendations.Some implementations may consider the negative relative-IOBcontributions differently from the positive relative-IOB contributions.

In other implementations, the previously described automated deliveryand associated automated IOB may be replaced with an “overall” deliveryand associated overall IOB. In some embodiments, this overall deliveryincludes both the automated delivery and the manual delivery of insulinscheduled by the user or caregiver. For example, an overall deliverycould include a temporary basal rate of x units of insulin per hour thatis manually specified to be different from a reference delivery scheduleof z units of basal delivery per hour. In these implementations, arelative-IOB for this type of overall delivery is calculated bycomputing the IOB for both the overall delivery (IOB_overall) and forthe reference delivery over the same time period (IOB_reference) andthen taking the difference, IOB_overall-IOB_reference to find therelative-IOB to assign to the period of the overall delivery. Typically,the IOB_overall and IOB_reference calculations will include all insulindosing including basal insulin doses during the time period underconsideration. The same calculation may be performed by first taking thedifference between the overall delivery and the reference deliveryschedules to create a difference-in-delivery schedule. The IOB may becalculated on the difference-in-delivery schedule to compute therelative-IOB for the overall delivery. That is, the relative-IOBcalculation holds under the distributive property of mathematics. Itwill be apparent to those of ordinary skill in this art that othervariations to these calculations may be made without departing from thescope and spirit of the appended claims. In some of theseimplementations, the overall insulin on board value takes into accountall insulin delivered to the user prior to a specific time that isbelieved to not have been completely absorbed by the user prior to thatspecific time, including any and all basal doses delivered to the user.

A number of embodiments of the present disclosure have been described.Nevertheless, it will be understood that various modifications may bemade without departing from the spirit and scope of the disclosure.

For example, this specification contains many specific implementationdetails. However, these should not be construed as limitations on thescope of any inventions or of what may be claimed, but rather asdescriptions of features specific to particular embodiments of thepresent disclosure. Certain features that are described in thisspecification in the context of separate embodiments can also beimplemented in combination in a single embodiment. Conversely, variousfeatures that are described in the context of a single embodiment canalso be implemented in multiple embodiments separately or in anysuitable subcombination. Moreover, although features may be describedabove as acting in certain combinations and even initially claimed assuch, one or more features from a claimed combination can in some casesbe excised from the combination, and the claimed combination may bedirected to a subcombination or variation of a subcombination.

Similarly, while operations are depicted in the drawings anddescriptions in a particular order, this should not be understood asrequiring that such operations be performed in the particular ordershown or described, or in sequential order, or that all illustrated ordescribed operations be performed, to achieve desirable results. Incertain circumstances, multitasking and parallel processing may beadvantageous. Moreover, the separation of various system components inthe embodiments described above should not be understood as requiringsuch separation in all embodiments, and it should be understood that thedescribed program components and systems can generally be integratedtogether in a single software product or packaged into multiple softwareproducts.

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessorstructures, and any one or more processors of any kind of digitalcomputer. Generally, a processor will receive instructions and data froma read only memory or a random access memory or both. The elements of acomputer are a processor for performing actions in accordance withinstructions and one or more memory devices for storing instructions anddata. Generally, a computer will also include, or be operatively coupledto receive data from or transfer data to, or both, one or more massstorage devices for storing data, e.g., magnetic, magneto optical discs,or optical discs. However, a computer need not have such devices.Moreover, a computer can be embedded in another device, e.g., an insulinpump, an electronic pump controller, a continuous glucose monitor, amobile telephone or a personal digital assistant (PDA), to name just afew.

Devices suitable for storing computer program instructions and datainclude all forms of non volatile memory, media and memory devices,including, by way of example, semiconductor memory devices, e.g., EPROM,EEPROM, and flash memory devices; magnetic discs, e.g., internal harddisks or removable disks; magneto optical discs; and CD ROM and DVD-ROMdiscs. The processor and the memory can be supplemented by, orincorporated in, special purpose logic circuitry.

To provide for interaction with a user, embodiments of the subjectmatter described in this specification can be implemented on a computerhaving a display device, e.g., a CRT (cathode ray tube) or LCD (liquidcrystal display) monitor, for displaying information to the user and akeyboard and a pointing device, e.g., a mouse or a trackball, by whichthe user can provide input to the computer. Other kinds of devices canbe used to provide for interaction with a user as well; for example,feedback provided to the user can be any form of sensory feedback, e.g.,visual feedback, auditory feedback, or tactile feedback; and input fromthe user can be received in any form, including acoustic, speech, ortactile input. In addition, a computer can interact with a user bysending documents to and receiving documents from a device that is usedby the user; for example, by sending web pages to a web browser on auser's client device in response to requests received from the webbrowser. Thus, a user interface of the inventive systems and methodsdescribed herein may be remote from a computer-based processor of thesystem, and may be operated by a user and/or a caregiver.

Aspects of the disclosure can take the form of an entirely hardwareembodiment, an entirely software embodiment or an embodiment containingboth hardware and software elements. In some embodiments, aspects of thedisclosure are implemented in software, which includes, but is notlimited to, firmware, resident software, microcode, etc. Furthermore,the aspects of the disclosure can take the form of a computer programproduct accessible from a computer-usable or computer-readable mediumproviding program code for use by or in connection with a computer orany instruction execution system. For the purposes of this description,a computer-usable or computer-readable medium can be any tangibleapparatus that can contain, store, communicate, propagate, or transportthe program for use by or in connection with the instruction executionsystem, apparatus, or device.

As used herein, a computer-readable medium or computer-readable storagemedium, or the like, is intended to include hardware (e.g., registers,random access memory (RAM), non-volatile (NV) storage, to name a few),but may or may not be limited to hardware. The medium can be anelectronic, magnetic, optical, electromagnetic, infrared, orsemiconductor system (or apparatus or device) or a propagation medium.Examples of a computer-readable medium include a semiconductor or solidstate memory, magnetic tape, a removable computer diskette, a randomaccess memory (RAM), a read-only memory (ROM), a rigid magnetic disk andan optical disc. Current examples of optical discs include compactdisc-read-only memory (CD-ROM), compact disc-read/write (CD-R/W). Someportions of the detailed description may be presented in terms ofalgorithms and symbolic representations of operations on data or databits that may be, for example, within a computer memory. An algorithm ishere, and generally, conceived to be a self-consistent sequence ofoperations leading to a desired result. The operations are thoserequiring physical manipulations of physical quantities. Usually, thoughnot necessarily, these quantities take the form of electrical ormagnetic signals capable of being stored, transferred, combined,compared, and otherwise manipulated. It has proven convenient at times,principally for reasons of common usage, to refer to these signals asbits, values, elements, symbols, characters, terms, numbers, or thelike.

It should be borne in mind, however, that these and similar terms are tobe associated with the appropriate physical quantities and are merelyconvenient labels applied to these quantities. Unless specificallystated otherwise or as apparent from context, it is appreciated thatthroughout the description, discussions utilizing terms such as“processing” or “computing” or “calculating” or “determining” or“displaying” or the like, refer to the action and processes of acomputer system, or similar electronic computing device, computer-basedprocessor, etc., which manipulates and transforms data represented asphysical (electronic) quantities within the computer system's registersand memories into other data similarly represented as physicalquantities within the computer system's memories or registers or othersuch information storage, transmission or display devices.

Other embodiments are within the scope of the appended claims.

What is claimed is:
 1. An insulin delivery system, comprising: a glucosemonitor; an insulin delivery device; and a remote device in wirelesscommunication with the glucose monitor and the insulin delivery device,the remote device comprising: at least one processor; and anon-transitory computer-readable storage medium storing instructionsthereon that, when executed by the processor, cause the remote deviceto: determine an estimated insulin-on-board (IOB) based at leastpartially on insulin delivery information related to a person withdiabetes (PWD); and determine a relative IOB that represents adifference between a reference IOB and the estimated IOB, the referenceIOB representing an amount of insulin required to maintain blood glucosestasis of the PWD; and determine a recommended bolus dose of insulin,comprising: based at least partially on the determined relative IOB,projecting future blood glucose levels for one or more changes to basalinsulin delivery to the PWD; and based at least partially on projectedfuture blood glucose levels, determining whether the recommended bolusdose of insulin is necessary to achieve a target blood glucose level. 2.The insulin delivery system of claim 1, wherein the remote devicefurther comprises instructions that, when executed by the processor,cause the remote device to receive measured blood glucose levels of thePWD from the glucose monitor.
 3. The insulin delivery system of claim 1,wherein the remote device further comprises instructions that, whenexecuted by the processor, cause the remote device to, responsive todetermining that the recommended bolus dose of insulin is necessary toachieve a target blood glucose level, provide the recommended bolus doseof insulin to the PWD.
 4. The insulin delivery system of claim 1,wherein the remote device further comprises instructions that, whenexecuted by the processor, cause the remote device to, responsive todetermining that the recommended bolus dose of insulin is unnecessary toachieve a target blood glucose level, discard the recommended bolus doseof insulin.
 5. The insulin delivery system of claim 1, wherein theremote device further comprises instructions that, when executed by theprocessor, cause the remote device to: project a first set of futureblood glucose levels based, at least in part, on an anticipated mealintake; and project a second set of future blood glucose levelsresponsive to the assumed one or more changes to basal insulin deliveryto the PWD.
 6. The insulin delivery system of claim 5, wherein theremote device further comprises instructions that, when executed by theprocessor, cause the remote device to determine a meal bolus dose based,at least in part, on a difference between the second set of future bloodglucose levels and the target blood glucose level.
 7. The insulindelivery system of claim 1, wherein the remote device further comprisesinstructions that, when executed by the processor, cause the remotedevice to: receive measured blood glucose levels of the PWD from theglucose monitor; and responsive to determining that the receive measuredblood glucose levels of the PWD are outside of a target range of bloodglucose levels, determine a correction dose of insulin.
 8. The insulindelivery system of claim 1, wherein the assumed one or more changes tobasal insulin delivery comprise one of an increase in basal insulindelivery or a decrease in basal insulin delivery.
 9. The insulindelivery system of claim 1, wherein determining that the recommendedbolus dose of insulin is necessary to achieve a target blood glucoselevel comprises: determining that received measured blood glucose levelsare outside of a target range for blood glucose levels; and determiningthat that delivery of the recommended bolus dose of insulin will bringthe blood glucose levels of the PWD within the target range for bloodglucose levels.
 10. The insulin delivery system of claim 1, whereindetermining that the recommended bolus dose of insulin is necessary toachieve a target blood glucose level comprises determining that deliveryof the recommended bolus dose of insulin will compensate for projectedincreased blood glucose levels due to an anticipated meal and willmaintain blood glucose levels of the PWD within a target range for bloodglucose levels.
 11. A method for managing insulin delivery, comprising:determining an estimated insulin-on-board (IOB) based at least partiallyon insulin delivery information related to a person with diabetes (PWD);determining a relative IOB that represents a difference between areference IOB and the estimated IOB, the reference IOB representing anamount of insulin required to maintain blood glucose stasis of the PWD;determining a recommended bolus dose of insulin, comprising: based atleast partially on the determined relative IOB, projecting future bloodglucose levels for one or more changes to basal insulin delivery to thePWD; and based at least partially on projected future blood glucoselevels, determining whether the recommended bolus dose of insulin isnecessary to achieve a target blood glucose level.
 12. The method ofclaim 11, further comprising, responsive to determining that therecommended bolus dose of insulin is necessary to achieve a target bloodglucose level, providing the recommended bolus dose of insulin to thePWD.
 13. The method of claim 11, further comprising, responsive todetermining that the recommended bolus dose of insulin is unnecessary toachieve a target blood glucose level, discarding the recommended bolusdose of insulin.
 14. The method of claim 11, further comprising:projecting a first set of future blood glucose levels based, at least inpart, on an anticipated meal intake; and projecting a second set offuture blood glucose levels responsive to the assumed one or morechanges to basal insulin delivery to the PWD.
 15. The method of claim14, further comprising determining a meal bolus dose based, at least inpart, on a difference between the second set of future blood glucoselevels and the target blood glucose level.
 16. The method of claim 11,further comprising: receiving measured blood glucose levels of the PWDfrom a glucose monitor; and responsive to determining that the receivedmeasured blood glucose levels of the PWD are outside of a target rangeof blood glucose levels, determining a correction dose of insulin. 17.The method of claim 11, wherein projecting future blood glucose levelsassuming one or more changes to basal insulin delivery to the PWDcomprises: assuming an increase in basal insulin delivery; or assuming adecrease in basal insulin delivery.
 18. The method of claim 11, whereindetermining that the recommended bolus dose of insulin is necessary toachieve a target blood glucose level comprises: determining thatreceived measured blood glucose levels are outside of a target range forblood glucose levels; and determining that that delivery of therecommended bolus dose of insulin will bring the blood glucose levels ofthe PWD within the target range for blood glucose levels.
 19. The methodof claim 11, wherein determining that the recommended bolus dose ofinsulin is necessary to achieve a target blood glucose level comprisesdetermining that delivery of the recommended bolus dose of insulin willcompensate for projected increased blood glucose levels due to ananticipated meal and will maintain blood glucose levels of the PWDwithin a target range for blood glucose levels.
 20. A remote device forassisting in insulin delivery, the remote device comprising: at leastone processor; and a non-transitory computer-readable storage mediumstoring instructions thereon that, when executed by the processor, causethe remote device to: determine an estimated insulin-on-board (IOB) fora person with diabetes (PWD); and determine a difference between areference IOB and the estimated IOB, the reference IOB representing anamount of insulin required to maintain blood glucose stasis of the PWD;and based at least partially on the difference between the reference IOBand the estimated IOB, project future blood glucose levels assuming oneor more changes to basal insulin delivery to the PWD; and based at leastpartially on projected future blood glucose levels, determining whetheran unscheduled bolus dose of insulin will be necessary to achieve atarget blood glucose level for the PWD.